Software testing process is a crucial part in software development. Generally the errors
made by developers get fixed at a later stage of the software development process. This …

The past 10 years have seen the prediction of software defects proposed by many
researchers using various metrics based on measurable aspects of source code entities (eg …

Software defect prediction has been an important research topic in the software engineering
field, especially to solve the inefficiency and ineffectiveness of existing industrial approach of …

Context: Software defect prediction (SDP) models help in delivering a dependable and a
genuine product to the clients. However, the performance of these models is affected by the …

In this paper, we study the learning impact of data sampling followed by attribute selection
on the classification models built with binary class imbalanced data within the scenario of …

Abstract Software Defect Prediction (SDP) is an important method to analyze software
quality and reduce development cost. Data from software life cycle has been widely used to …

Context Software defect prediction means finding defect-prone modules before the testing
process which will reduce testing cost and time. Machine learning methods can provide …

Software defect prediction enhances the quality, efficiency, and effectiveness of time and
expenses for software testing by focusing on defect modules. Software defect prediction …

Software engineering activities comprise of several activities to ensure that the quality
product will be achieved at the end. Some of these activities are software testing, inspection …

Classification techniques is a popular approach to predict software defects and it involves
categorizing modules, which is represented by a set of metrics or code attributes into fault …